region_growing

非精确ALM解决PCA算法的例子，用后效果不错，发上来分享。(This matlab code implements the inexact augmented Lagrange multiplier method for Robust PCA.)

基于人眼视觉的图像融合方法 很好很经典 符合人眼视觉特性(Based on the human visual image fusion method)

利用加权矩阵的盲超分辨率方法重建出一幅高分辨率的图像(The weighted matrix method of blind super-resolution reconstruction of a high-resolution image)

这个程序实现了光流法对运动物体的识别，效果还行(This program implements the optical flow method to identify moving objects, the results were OK)

说明：  通过用户给定的标签信息，来提取图像中的标记像素点位置，保存为种子点(Through the label information given by the user, the position of the label pixels in the image is extracted and saved as seed points.)

一个短小精悍的分水岭算法,用Matlab实现,程序简单易懂(A dapper watershed algorithm, using Matlab implementation, the program easy-to-read)

对输入图片进行LBP特征提取，并实现LBP特征可视化( U5BF9 u8F93 u5161 u5D3 u53D3 u53E0 )

一套完整的图像处理与识别的源码（全中文注释） 这是我们内部开发与使用的一套图像处理代码，里面包括了大部分图像处理与识别处理的的函数：像模板变换，图像的平滑、锐化、边缘识别、图像中值滤波、图像模糊、图像逆滤波、图像模糊加噪、图像维纳滤波、线性变换、灰度拉伸、直方图均衡、图像腐蚀、图像膨胀、图像开运算、GIF确码编码、缩放、旋转、快速付立叶变换、离散余弦变换等等，等等，太多了。可以用于windows软件或嵌入式软件编程。内部用的，全中文注释，为了下载我才拿出来的。你们自己看着办吧。(a complete set of image processing and recognition of the source code (all Chinese Note) This is our internal development and use of a image processing code, includes the most image processing and recognition processing function : as template transform, Image smoothing, sharpening, edge recognition, image filtering and fuzzy images, image inverse filtering, fuzzy image noise increases, Wiener filter images, linear transformation, gray tensile, histogram equalization, images corrosion, expansive images, image open operation, GIF correct coding, zooming, rotation, fast Fourier transform, discrete cosine transform, and so on and so forth, that is too many. Can be used for windows software or embedded software programming. Internal use, and the whole Chinese translations, in order to download )

Tamura纹理特征提取及应用的matlab代码，附有介绍绍Tamura纹理的文献和测试用图片。，已通过测试。 (Tamura texture feature extraction and application of the Matlab code, accompanied by Shao Tamura texture literature and test pictures. , Has been tested.)

基于Mean Shift的图像分割过程就是首先利用Mean Shift算法对图像中的像素进行聚类，即把收敛到同一点的起始点归为一类，然后把这一类的标号赋给这些起始点，同时把包含像素点太少的类去掉。然后，采用阈值化分割的方法对图像进行二值化处理 (Mean Shift Based on the process of image segmentation is the first to use the image Mean Shift algorithm for clustering of pixels, that is, to converge to the same point as a starting point to the category and then assigned to this type of labeling of these starting points, at the same time to contain too few pixels to remove the category. Then, using thresholding segmentation method of binary image processing)